Learning with “Microworlds” (Middle School)

What if a science teacher could base the pace of her classroom instruction precisely on whether each student successfully solves the assignment at hand?

Thanks to recent progress by a Learning Sciences research group at the Worcester Polytechnic Institute in Massachusetts, this dream is no longer hypothetical. By harnessing the power of a computerized science assessment and tutoring system weâve developed in collaboration with other colleagues, middle school teachers can now use a handheld smartphone to find out whether Johnny Smith at, say, desk 6, is struggling with the formation of a basic hypothesis, or conducting experimental trials.

Our program is in its fifth year of development for assessments for Physical, Earth, and Life Sciences in accordance with goals of the Massachusetts Curricular Frameworks. Recently, weâve advanced to real-time tutoring for Physical Science based on studentsâ assessment data. Even though the approach to tutoring in real time is new, the idea looks promising so far.

Our tutoring environment deploys a series of âmicroworldsâ designed to engage middle school students with simulated laboratory environments. Each microworld lab allows students to virtually conduct inquiry within a science topic. This means that, instead of pouring actual fluid content from a beaker into a flask, each student can simulate the process using virtual equipment, materials, etc.

Within each microworld activity, students form a hypothesis, design an experiment, conduct the experiment, analyze their data, warrant their claims with data, and then communicate their findings.

In real time, data, a graph and calculations are displayed for the student on their computer screen. Also along the way, the microworld environment provides various tools, such as widgets for changing variables that guide each student. Weâve even crafted a tool we call a âhypothesis builderâ that uses a series of changeable drop-down menus that, when completed, will provide a hypothesis worthy of experiment.

And because the data are web-based and can be aggregated at various levels (e.g., the class level, the student level, etc.), teachers can track each studentâs progress dynamically from their own monitoring device, such as a smart phone, at a very fine granular level.

Think about it: While students work through each stage of inquiry, the teacher can âlook over their shoulderââvirtually, of courseâand know whether they are developing sound fundamental skills underlying scientific inquiry. Are they testing the hypothesis they said they were going to test? Are they using the proper âcontrol-for-variablesâ strategy? Are they making the correct interpretation from their data? Can they choose the correct trials that support this conclusion?

Through logging studentsâ actions, these data provide a wealth of useful data about student skills, both in process and the end product, which are used in turn by teachers to inform their instruction.

We think this program optimizes a visuo-spatial form of learning: In any text problem, the textÂ is non-isomorphic to the thing it represents. In a virtual microworld, each thing is isomorphic to what it represents in science at varying levels of abstraction.

These microworlds illuminate for students complex processes that are otherwise invisible to the human eyeâbecause of their size scale or time scaleâin areas like phase change, cellular biology, mountain formation and even more abstract topics, such as how convection currents form.

With so much interest of late on visual and inquiry-based learning, this is an interesting and engaging way for students to learn science through inquiry. We hope very soon to produce efficacy data about our approach to real-time tutoring.